GEO explained clearly
What is Generative Engine Optimization?
Generative Engine Optimization, or GEO, means work on the discoverability and interpretation of content in generative answer systems. It concerns relevant information, clear business details and the actual use of sources in AI answers.
What changes with an AI answer
A traditional search results page shows a selection of results. A generative answer system can process information into a coherent answer and link sources. Its specific operation depends on the service, available research function and question asked.
This creates several possible forms of visibility for businesses. The company name may appear in the text, the business may be presented as an option or one of its pages may appear as a source. These events differ and should be measured separately.
How GEO and SEO relate
In many cases, GEO builds on familiar website foundations: content must be accessible, helpful and clearly structured. Unambiguous business information and relevant internal links support orientation. Basic SEO requirements remain relevant for Google Search’s AI features.
The additional perspective concerns answers and source references. While SEO examines factors including search impressions and clicks, GEO also examines mentions, recommendations and citations within a documented question set. A good Google position does not automatically prove a recommendation in every AI application.
Which content is useful for a business
- Company introduction: Who is responsible, where is the actual business address and how can people make contact?
- Service pages: Who is the offering suitable for, what does it include and how does collaboration begin?
- Decision support: Which criteria, prerequisites and limitations should prospects know?
- Evidence: Which real examples or results can be presented with accurate context?
- Terminology: Which specialist terms need explanation so customers can make a decision?
This content first serves a purpose for people. Optimisation does not mean hiding instructions for AI systems or artificially repeating your own name.
A practical example without invented success figures
Illustrative example: A Swiss business advises small and medium-sized companies on changing their accounting software. A helpful website explains which existing systems are considered, which documents are needed and how data migration, training and handover work.
An additional guide can explain selection criteria or typical project questions. This creates clearly assigned information for a specific need. Whether an AI system uses these pages must subsequently be observed in practice. The example is neither a case study nor evidence of an effect.
What GEO cannot guarantee
Source selection and answer wording are controlled by the respective system. Results may differ between questions, times and interfaces. An agency can improve content and technology but cannot guarantee lasting mentions for all users.
Individual technical files are no substitute for this work either. Google Search ignores llms.txt; actual use by other systems must be checked individually. Structured data describes content but creates no automatic entitlement to recommendations.
Start with a manageable question
Choose an important service, collect related customer questions and examine which answers your website already provides. Missing content and technical questions can then be prioritised. A baseline observation should document what was actually checked.
The GEO service page explains a possible project process. For evaluation, the guide Measuring AI visibility can help; specialist terms are explained in the glossary.
Assess AEO, GEO and LLMO by the actual task
Offers and specialist articles use several labels for work on answers and AI visibility. Their applications overlap. An acronym alone therefore does not describe a clear commission.
| Label | What you should clarify specifically |
|---|---|
| AEO – Answer Engine Optimization | The term emphasises direct answers. Which user question and result format should actually be examined? |
| GEO – Generative Engine Optimization | It concerns content and businesses in generative answers. Which systems, questions and source relationships belong in the agreed scope? |
| LLMO – Large Language Model Optimization | The term is used for optimisation around large language models. Which application, content and verifiable changes are meant? |
AI Overviews is a Google Search feature. If only “AIO” is mentioned, ask for the intended term to be written out and the interface checked to be named. Basic SEO requirements remain relevant for AI Overviews and AI Mode; Google requires neither special AI files nor dedicated schema markup for them. Source: Google on AI features and websites.
Ask an offer’s provider about specific deliverables, data and acceptance criteria. A promised place in the training knowledge of someone else’s model is not a controllable website deliverable. The glossary explains the difference between source retrieval with RAG and additional model training.
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